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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Quantum mixed state compiling

The task of learning a quantum circuit to prepare a given mixed state is a fundamental quantum subroutine. We present a variational quantum algorithm (VQA) to learn mixed states which is suitable for near-term hardware. Our algorithm represents a generalization of previous VQAs that aimed at learning preparation circuits for pure states. We consider two different ansätze for compiling the target state; the first is based on learning a purification of the state and the second on representing it as a convex combination of pure states. In both cases, the resources required to store and manipulate the compiled state grow with the rank of the approximation. Thus, by learning a lower rank approximation of the target state, our algorithm provides a means of compressing a state for more efficient processing. As a byproduct of our algorithm, one effectively learns the principal components of the target state, and hence our algorithm further provides a new method for principal component analysis. We investigate the efficacy of our algorithm through extensive numerical implementations, showing that typical random states and thermal states of many body systems may be learnt this way. Additionally, we demonstrate on quantum hardware how our algorithm can be used to study hardware noise-induced states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mixing effects on spectroscopy and partonic observables of heavy mesons with logarithmic confining potential in a light-front quark model

Using the variational principle, we systematically investigate the mass spectra and wave functions of both 1⁢𝑆 and 2⁢𝑆 state heavy pseudoscalar (𝑃) and vector (𝑉) mesons within the light-front quark model. This approach incorporates a Coulomb plus logarithmic confinement potential to accurately describe the constituent quark and antiquark dynamics. Additionally, spin hyperfine interactions are introduced perturbatively to compute the masses of pseudoscalar and vector mesons. The present analyses of the 1⁢𝑆 and 2⁢𝑆 states require the consideration of mixing between them to account for empirical constraints. These constraints include the mass gap Δ⁢𝑀 𝑃 >Δ⁢𝑀 𝑉 , where Δ⁢𝑀 𝑃⁡(𝑉) =𝑀$^{2⁢𝑆}_{𝑃⁡(𝑉)}$−𝑀$^{1⁢𝑆}_{𝑃⁡(𝑉)}$ and the hierarchy of the decay constants 𝑓 1⁢𝑆 >𝑓 2⁢𝑆 . We find the optimal value of the mixing angle to be 𝜃 =1⁢8°, significantly enhancing the consistency between our spectroscopic predictions and the experimental data compiled by the Particle Data Group. Furthermore, based on the predicted mass, the newly observed resonance 𝐵 𝐽⁡ (5840) could be assigned as a 2 1⁢ 𝑆 0 state in the 𝐵 meson family. The study also reports various pertinent observables, including twist-two distribution amplitudes, electromagnetic form factors, charge radii, 𝜉 moments, and transition form factors that are found to be consistent with both available lattice simulations and experimental data. In addition, our predicted branching ratios for the channels of 𝐵 + →𝜏 + ⁢𝜈 𝜏 as well as rare decays of 𝐵 0 and 𝐵$^0_𝑠$ appear in accordance with experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Qompress: Efficient Compilation for Ququarts Exploiting Partial and Mixed Radix Operations for Communication Reduction

Quantum computing is in an era of limited resources. Current hardware lacks high fidelity gates, long coherence times, and the number of computational units required to perform meaningful computation. Contemporary quantum devices typically use a binary system, where each qubit exists in a superposition of the 0 and 1 states. Furthermore, it is often possible to access the 2 or even 3 states in the same physical unit by manipulating the system in different ways. In this work, we consider automatically encoding two qubits into one four-state ququart via a compression scheme. We use quantum optimal control to design efficient proof-of-concept gates that fully replicate standard qubit computation on these encoded qubits.

compilation↗

Geographic Information System in Bolivia: a Case Study for Latin America

Bolivia's Geological Service is concluding a successful project designed to give the Department of Oruro the capability to evaluate its natural resources using data generated by three United States satellites. A permanent integrated geographic information system was created for preparing base maps of soil characteristics, land use, geomorphology, geology, water resources and hydrology. The information compiled through the project was stored on magnetic disks and tapes to permit periodic updating, retrieval of data on specific aspects of development projects, and obtaining various data mixes to analyze aspects of prospective development projects. This is the first digital information system developed in Latin America.

Adrien, P. M.↗

VUV Photoionization Dynamics and Reactivity of Heterogeneous Water Clusters

This feature focuses on bridging isolated water and bulk water studies. It assembles experiments and theory on water clusters, mainly probed by vacuum ultraviolet (VUV) radiation, and summarizes what the effects are of intermolecular interactions on both the spectroscopy and the VUV-induced processes in water. In particular, it highlights studies of heterogeneous water clusters─those incorporating other molecular species such as naphthalene, methane, formic acid, and glycerol─which serve as model systems to investigate the fundamental roles of water in hydrogen bonding networks, proton transfer, and astrochemical processes. These mixed clusters provide a platform to revisit the stability of protonated water clusters and compile observations of ionization-induced structural rearrangements and fragmentation, especially in systems involving hydroxyl-rich cosolvents. This feature then explores energy transfer mechanisms in molecular clusters, following VUV photoexcitation. It concludes with potential future directions. First, we investigate excited-state dynamics in molecular clusters through direct probing, complementing the synchrotron studies discussed here. Second, exploring gas-phase molecule evaporation from confined spaces and interfaces using advanced spectroscopic techniques sheds light on these ubiquitous, yet currently debated, molecular processes.

Cluster chemistry↗

Dataset_for_Conserved_macromolecular_architecture_of_Poplar_secondary_cell_walls_revealed_by_ssNMR_and_atomistic_modeling

This dataset contains solid-state 13C NMR data and atomistic molecular dynamics simulation files supporting the study of nanoscale secondary cell wall architecture across 13 genetically diverse Populus trichocarpa genotypes grown under uniform greenhouse conditions in 13C-enriched CO2 atmospheres (~89% 13C enrichment).The dataset contains two collections of solid-state 13C NMR data. (1) 200 MHz data (Bruker Avance III HD, 4 mm HX probe, 10 kHz MAS): raw Bruker TopSpin experiment folders and DMFIT-exported ascii spectra for selective and non-selective 1D 13C-13C spin diffusion experiments (3000 ms mixing) used to quantify inter-polymer spatial proximities, and short-mixing (1 ms) reference spectra used for polymeric abundance quantification by spectral deconvolution. (2) 600 MHz data (Bruker Avance III, 1.6 mm PhoenixNMR HXY probe, 30 kHz MAS): raw Bruker TopSpin experiment folders containing 2D CORD, 2D CP-INADEQUATE, and 13C/1H relaxation (T1, T1rho) experiments for all 13 genotypes, with processed Excel workbooks per experiment type. Molecular dynamics simulation code, coordinate files, and analysis scripts (NAMD/CHARMM/Python) for six atomistic cell wall models are included. Summarized ssNMR data are compiled into a single excel file and subjected to statistical analysis. Multivariate analysis code (PCA, Pearson correlation) and summary data are provided as excel worksheets and Jupyter notebooks (Python 3).

09 BIOMASS FUELS↗

Singularity-EOS: Performance Portable Equations of State and Mixed Cell Closures

We present Singularity-EOS, a new performance-portable library for equations of state and related capabilities. Singularity-EOS provides a large set of analytic equations of state, such as the Gruneisen equation of state, and tabulated equation of state data under a unified interface. It also provides support capabilities around these equations of state, such as Python wrappers, solvers for finding pressure-temperature equilibrium between multiple equations of state, and a unique modifier framework, allowing the user to transform a base equation of state, for example by shifting or scaling the specific internal energy. All capabilities are performance portable, meaning they compile and run on both CPU and GPU for a wide variety of architectures.

97 MATHEMATICS AND COMPUTING↗

FLASH: FPGA-Accelerated Smart Switches with GCN Case Study

Some communication switches, e.g., the Mellanox SHArP and those in the IBM BlueGene clusters, are augmented to process packets at the application level with fixed-function collectives. This approach, however, lacks flexibility, which limits their applicability in diverse and dynamic workloads. Recently, a new type of programmable packet processor, which uses high-level languages, e.g., P4, has emerged as possible candidates. P4-based switches, however, fall short in certain applications, including machine learning, where capabilities not currently supported by P4 are needed. These include more complex calculation, such as sparse computation and fused multiply-accumulate, data-intensive floating point operations, data reuse, and significant memory. The problem addressed here is that such a switch augmentation needs to support: a large amount of state, significant flexible compute capability, and ease of programming, all while maintaining full functionality, including ensuring high throughput, and demonstrating utility. In this work, we propose a programmable look-aside-type accelerator that can be embedded into, or attached to, existing communication switch pipelines and that is capable of processing packets at line-rate. The proposed in-switch accelerator is based on mixing an ISA (subset of RISC-V instructions) with dataflow graphs (found in CGRAs). To augment performance, vector instructions are also supported. To facilitate usability, we have developed a complete toolchain to compile user-provided C/C++ codes to appropriate back-end instructions for configuring the accelerator. While this approach is flexible enough to support various workloads, in this paper, we consider Graph Convolutional Networks (GCNs) as a case study. Experimental results show that this approach considerably improves the performance of distributed GCN applications.

Haghi, Pouya↗

Symmetry and Error Mitigation in Quantum Alternating Operator Ansatz

Quantum Alternating Operator Ansatz (QAOA) provides a platform for probing quantum advantage in optimization problems on NISQ hardware. By exploring symmetries in the system and the structure of unitaries in the algorithm, we proposed using problem-specific mixing operators to limit the quantum evolution within a subspace where the target state lives. As an example, in case of equality constraint, we studied the use of XY operators that preserve total Pauli Z. This QAOA variant, in the noiseless case, significantly outperforms the vanilla version of QAOA where the constraints are encoded as penalty in the cost Hamiltonian and the search is in the whole Hilbert space. In presence of noise, although the advantage still holds, error mitigation is needed for QAOA. I will overview our work on the design of QAOA in presence of symmetry, the implementation and compilation of XY-QAOA, its performance and error mitigation techniques in presence of noise.

Zhihui Wang↗

Mapping Spiking Neural Networks to Heterogeneous Crossbar Architectures using Integer Linear Programming

Advances in novel hardware devices and architectures allow Spiking Neural Network (SNN) evaluation using ultra-low power, mixed-signal, memristor crossbar arrays. As individual network sizes quickly scale beyond the dimensional capabilities of single crossbars, networks must be mapped onto multiple crossbars. Crossbar sizes within modern Memristor Crossbar Architectures (MCAs) are determined predominately not by device technology but by network topology; more, smaller crossbars consume less area thanks to the high structural sparsity found in larger, brain-inspired SNNs. Motivated by continuing increases in SNN sparsity due to improvements in training methods, we propose utilizing heterogeneous crossbar sizes to further reduce area consumption. This approach was previously unachievable as prior compiler studies only explored solutions targeting homogeneous MCAs. Our work improves on the state-of-the-art by providing Integer Linear Programming (ILP) formulations supporting arbitrarily heterogeneous architectures. By modeling axonal interactions between neurons, our methods produce better mappings while removing inhibitive a priori knowledge requirements. We first show a 16.7-27.6% reduction in area consumption for square-crossbar homogeneous architectures. Then, we demonstrate 66.9-72.7% further reduction when using a reasonable configuration of heterogeneous crossbar dimensions. Next, we present a new optimization formulation capable of minimizing the number of inter-crossbar routes. When applied to solutions already near-optimal in area, an 11.9-26.4% routing reduction is observed without impacting area consumption. Finally, we present a profile-guided optimization capable of minimizing the number of runtime spikes between crossbars. Compared to the best-area-then-route optimized solutions, we observe a further 0.5-14.8% inter-crossbar spike reduction while requiring 1–3 orders of magnitude less solver time.

Pohl, Devin [ORNL] (ORCID:0009000040149027)↗

Determining Exact RANS Operators with the Macroscopic Forcing Method (Final Report)

This report contains a compilation of key results and findings from the ACT project “Determining Exact RANS Operators with the Macroscopic Forcing Method.” The Macroscopic Forcing Method (MFM), a numerical tool for determining closure operators, is used to measure eddy diffusivity moments in Rayleigh-Taylor (RT) instability. It is first applied to low-Atwood 2D RT instability; that work is then extended to 3D RT at different finite Atwood numbers. It is found that nonlocality is important for modeling the mean scalar transport closure operator in RT mixing. Additionally, work is done to improve the statistical convergence of MFM for chaotic problems like RT mixing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Propionitrile in the Two Lowest Excited Vibrational States in the Laboratory and on Titan

The rotational spectrum of propionitrile (ethyl cyanide, C2H5CN) in the two lowest excited vibrational states, ν(sub 13) = 1 and ν(sub 21) = 1, was studied in detail. The compiled experimental data set consisted of published line lists, lines measured from published spectra up to 645 GHz, and new measurements at frequencies from 8 to 331 GHz. The two states are subject to considerable mutual interaction but application of a- and b-axis Coriolis coupling model to the measured A-symmetry internal rotation substate transitions was found to be successful. A total of over 1900 transitions were fitted for J values up to 76 and Ka up to 24, resulting in determined vibrational separation between the two states ΔE = 6:2070246(14) cm(exp -1), and Coriolis coefficients |ζ(sup a)(sub 13,21)| = 0.378, |ζ(sup b) (sub 13,21)| = 0.127, in good agreement with quantum chemistry calculations. The new line catalog was used to model ALMA spectra of Titan’s atmosphere from 2016, fitting many weak lines not previously modeled. By including the vibrationally excited lines of C2H5CN and a new partition function, we derive a disk-averaged volume mixing ratio estimate in 2016 of 7.8 ± 0.2 ppb assumed constant above 300 km.

Analysis of rotational spectrum↗

Analyzing Carbon Dioxide and Methane Emissions in California Using Airborne Measurements and Model Simulations

Greenhouse gas (GHG) concentrations have increased over the past decades and are linked to global temperature increases and climate change. These changes in climate have been suggested to have varying effects, and uncertain consequences, on agriculture, water supply, weather, sea-level rise, the economy, and energy. To counteract the trend of increasing atmospheric concentrations of GHGs, the state of California has passed the California Global Warming Act of 2006 (AB-32). This requires that by the year 2020, GHG (e.g., carbon dioxide (CO2) and methane (CH4)) emissions will be reduced to 1990 levels. To quantify GHG fluxes, emission inventories are routinely compiled for the State of California (e.g., CH4 emissions from the California Greenhouse Gas Emissions Measurement (CALGEM) Project). The major sources of CO2 and CH4 in the state of California are: transportation, electricity production, oil and gas extraction, cement plants, agriculture, landfills/waste, livestock, and wetlands. However, uncertainties remain in these emission inventories because many factors contributing to these processes are poorly quantified. To alleviate these uncertainties, a synergistic approach of applying air-borne measurements and chemical transport modeling (CTM) efforts to provide a method of quantifying local and regional GHG emissions will be performed during this study. Additionally, in order to further understand the temporal and spatial distributions of GHG fluxes in California and the impact these species have on regional climate, CTM simulations of daily variations and seasonality of total column CO2 and CH4 will be analyzed. To assess the magnitude and spatial variation of GHG emissions and to identify local “hot spots”, airborne measurements of CH4 and CO2 were made by the Alpha Jet Atmospheric eXperiment (AJAX) over the San Francisco Bay Area (SFBA) and San Joaquin Valley (SJV) in January and February 2013 during the Discover-AQ-CA study. High mixing ratios of GHGs were observed in-flight with a high degree of spatial variability. To provide an additional method to quantify GHG emissions, and analyze AJAX measurement data, the GEOS-Chem CTM is used to simulate SFBA/SJV GHG measurements. A nested-grid version of GEOS-Chem will be applied and utilizes varying emission inventories and model parameterizations to simulate GHG fluxes/emissions. The model considers CO2 fluxes from fossil fuel use, biomass/biofuel burning, terrestrial and oceanic biosphere exchanges, shipping and aviation, and production from the oxidation of carbon monoxide, CH4, and non-methane volatile organic carbons. The major sources of CH4 simulated in GEOS-Chem are domesticated animals, rice fields, natural gas leakage, natural gas venting/flaring (oil production), coal mining, wetlands, and biomass burning. Preliminary results from the comparison between available observations (e.g., AJAX and CALGEM CH4 emission maps) and GEOS-Chem results will be presented, along with a discussion of CO2 and CH4 source apportionment and the use of the GEOS-Chem-adjoint to perform inverse GHG modeling.

Johnson, Matthew S.↗

TankSIM: A Cryogenic Tank Performance Prediction Program

Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

Bolshinskiy, L. G.↗

A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

LLVM↗

Lunar impact basins: New data for the nearside northern high latitudes and eastern limb from the second Galileo flyby

During the December 1992 Galileo Earth/Moon encounter the northern half of the nearside, the eastern limb, and parts of the western farside of the Moon were illuminated and in view, a geometry that was complementary to the first lunar encounter in December, 1990, which obtained images of the western limb and eastern farside. The Galileo Solid State Imaging System (SSI) obtained multispectral images for these regions during the second encounter and color ratio composite images were compiled using combinations of band ratios chosen on the basis of telescopic spectra and laboratory spectra of lunar samples. Ratios of images taken at 0.41 and 0.76 micron are sensitive to changes in the slope in the visible portion of the spectrum, and ratios of 0.99 and 0.76 micron relate to the strength of near-infrared absorptions due to iron-rich mafic minerals (0.76/0.99 ratio) such as olivine and pyroxene. Results of the analyses of the compositional diversity of the crust, maria, and Copernican craters are presented elsewhere. Primary objectives for lunar basin analysis for the second encounter include analysis of: the north polar region and the Humboldtianum basin; the characteristics of the Imbrium basin along its northern border and the symmetry of associated deposits; the origin of light plains north of Mare Frigoris and associated with several other basins; the nature and significance of pre-basin substrate; the utilization of the stereo capability to assess subtle basis structure; the identification of previously unrecognized ancient basins; basin deposits and structure for limb and farside basins; and assessment of evidence for proposed ancient basins. These data and results will be applied to addressing general problems of evaluation of the nature and origin of basin deposits, investigation of mode of ejecta emplacement and ejecta mixing, analysis of the origin of light plains deposits, analysis of basin deposit symmetry/asymmetry, investigation of basin depth of excavation and crustal stratigraphy, and assessment of models for basin formation and evolution. Here we discuss some preliminary results concerning lunar impact basins, their deposits, and prebasin substrates, using the same approaches that we employed for the Orientale and South Pole-Aitken basins using the data from the first encounter.

Head, J. W.↗

Data driven investigation to understand the influence of total solids on biological biogas upgrading

In situ biogas upgrading achieves CO 2 conversion to CH 4 via hydrogenotrophic methanogenesis; however, gas-liquid mass transfer constraints limit the upgrading performance. Recognizing that optimization studies often underrepresent the effects of total solids (TS) and organic loading rate (OLR), this study undertook a holistic, statistics driven assessment of operating conditions for in situ H 2 assisted biogas upgrading, centering the analysis on TS and OLR. A dataset of 31 studies was compiled and comprised 99 observations. A rigorous analytical framework was employed, combining data standardization, fixed- and random-effects (REML) weighted regressions with cluster-robust errors, stratified analyses, and machine learning. Mixed-effects meta regression indicated that TS was the main factor explaining differences of methane fraction (CH 4 %) when considering the between studies heterogeneity. Focusing on a near-stoichiometric subset (H 2 /CO 2 ≈ 4:1), TS remained significant. Stratified results showed a stronger negative relationship between TS and CH 4 % in UASB reactors than in CSTRs, with a negative effect under mesophilic conditions and no significant effect under thermophilic conditions. A Random Forest model corroborated the statistical findings, consistently ranking H 2 /CO 2 ratio, OLR, TS, and hydrogen injection rate (HIR) as the most influential predictors. These findings delineate trends across increasing TS levels, particularly between 1% and 10%, and provide preliminary insights for TS above 15% in in situ biogas upgrading. They further provide insights for the influence of TS by reactor type and temperature, thereby advancing the evidence base for implementing biological CO 2 conversion to CH 4 in practice.

In situ biogas upgrading↗

Assessing hydrogen supply chains: An integrated review of leakage and energy efficiency studies

This paper examines hydrogen leakage and efficiency across the supply chain for liquid, gaseous, and mixed hydrogen systems. These factors are crucial for assessing hydrogen's role in mitigating emissions and facilitating a clean energy transition. Drawing on a comprehensive review of existing literature and model-based analysis, the study compiles leakage rates and efficiency metrics at each stage of the supply chain: production, storage, transmission, distribution, and end-use. These data inform system scenarios that estimate the impact of leakage on overall performance and climate benefits. The analysis also identifies persistent data gaps, particularly for liquid and mixed system configurations, and outlines priorities for future research. A comparison of hydrogen system types shows that gaseous pathways generally achieve the highest efficiencies (28 %–39 %) and the lowest leakage rates (∼4.5 %) across the supply chain. Liquid hydrogen systems, while favorable for long-distance and high-volume transport due to their higher energy density, exhibit lower efficiency (∼28 %) and a greater leakage potential (∼12 %). Mixed systems, which combine gaseous and liquid elements (e.g., pipeline transmission followed by liquefaction and truck distribution), show compounded energy losses and moderate-to-high leakage rates (6.8 %–9.4 %), highlighting trade-offs associated with added system complexity. The study highlights opportunities for technological advancements, including optimizing liquefaction, enhancing insulation for storage and transportation, and refining refueling equipment. These improvements are crucial for maximizing the climate benefits of hydrogen. The results offer actionable insights for researchers, industry, and policymakers working to develop low-leakage, high-efficiency hydrogen infrastructure.

08 HYDROGEN↗